Assessment Of Brain Function And Estimation Of Prognosis For Patients With Disorders Of Consciousness

Advances in technology and intensive care have led to an increase in the number ofpatients who survive severe brain injury, resulting in the increase in the number of patientswith disorders of consciousness (DOC). Disorders of consciousness include Coma,vegetative state (VS) and minimally conscious state (MCS). Such patients often requirelong-term intensive care in order to survive, which often results in familial, economic, andsocial consequences. Accurate and reliable prognosis assessment can provide families andclinicians with useful outcome information. The most commonly used methods are clinicalscales, which based on behavioral assessment. These methods lack objective, and need tobe repeated assessments to reduce their deviation. Serum biochemical parameters weremainly applied to the acute brain injury. These parameters displayed a gradual declineover time after brain injury, which indicates that they cannot be used as prognostic factorin the late phase of brain injury. Functional magnetic resonance imaging (fMRI) andpositron emission tomography (PET) are known and suggested variables, but the issues ofexpense and accessibility limit their use. Electrophysiological examination has greatadvantages; however, most of the current studies are small sample, a single-site research project.We performed series clinical prospective studies serving three proposes. First, we aimed tointegrate reliable behavioral and electrophysiological indicators to develop a simpleprognostic score for patients with VS. Second, we employed a thermal stimulationparadigm to assess the brain response by using fMRI and EEG in patients with VS andMCS, and further explored the role of this new method in the prognostication of outcome.Third, comparing with traditional coma, we put forward the concept of EEG-coma andconducted a prospective study of comatose patients to determine whether the EEG-comacan be used to predict awakening from coma or not.Part1Analysis of prognostic factors and development of a predictive score for thevegetative stateObjectives: Accurate outcome assessment for patients in vegetative state (VS) may helpclinicians and families guide the type and intensity of therapy; however, there is nosuitable and accurate means to predict the outcome so far. We aimed to develop a simplebedside scoring system to predict the likelihood of awareness recovery in VS.Methods: We prospectively enrolled56patients (age range10-73years) in VS during3-12weeks postonset. We collected demographic data and performed neurological,serological and neurophysiological tests at study entry. Each patient received6-monthfollow-up, during which awareness recovery was assessed by experienced physicians onthe basis of clinical criteria. Univariate and multivariable analyses were employed toassess the relationships between predictors and awareness recovery.Results: Twenty-four patients recovered awareness, among them3moderate disabilities,8severe disabilities,12minimally conscious state, and1dead after recovery. Twenty-threeremained in VS and9had died in VS. Motor response, type of brain injury,electroencephalogram reactivity, sleep spindles and N20were shown to be independent predictors for awareness recovery. Based on their coefficients in the model, we assignedthese predictors1point each and created a5-point score for prediction of awarenessrecovery. The resulting score showed good predictive accuracy in the derivation cohort.The area under the receiver operating characteristic curve for the score was0.918with87.50%sensitivity.Conclusions: This5-point score can be used to predict the probability of awarenessrecovery in VS, although it needs to be further confirmed in a larger sample.Part2Brain response to thermal stimulation predicts outcome of patients withchronic disorders of consciousnessObjectives: To study brain responses to thermal stimulation in functional magneticresonance imaging (fMRI) and electroencephalography (EEG) and their relationship toclinical outcomes of patients in vegetative state (VS) and minimally conscious state(MCS).Methods: We prospectively enrolled7healthy subjects and22patients, including10MCS and12VS. Thermal stimulation with warm water of42±2℃was applied duringfMRI and EEG reactivity (EEG-R) tests. Each patient received1-year follow-up, duringwhich the modified Glasgow Outcome Scale was used for outcome assessment.Results: Among22patients,1was lost to follow up,10had an improved outcome, andthe remaining11patients did not improve. Thermal stimulation induced3different brainactivation patterns in patients:(1) high-order activation (HA) in4patients, similar to thatin healthy controls;(2) primary activation (PA) in6patients; and (3) no activation (NA) in11patients. Eight of10patients with HA or PA had an improved outcome whereas only2of11patients with NA improved, suggesting that fMRI PA and HA had80%sensitivityand81.8%specificity to predict improved outcome. EEG-R to thermal stimulation waselicited in11patients and9of them have regained an improved outcome, while among10 patients with no EEG-R,9patients did not improve, showing that EEG-R had90%sensitivity and81.8%specificity to predict improved outcome.Conclusions: Brain responses to thermal stimulation can predict outcome of patients inVS or MCS with a high predictive accuracy.Part3Predictive value of EEG reactivity and sleep spindles for awakening fromcomaObjectives: In our previous study, we found that comatose patients those who lack EEGreactivity and/or sleep spindles always associated with poor outcome. So comparing withtraditional behavioral coma, we put forward the concept of EEG-coma defined as thedeficiency of EEG reactivity and/or sleep spindles. We conducted a prospective study ofcomatose patients to determine whether the EEG-coma can be used to predict awakeningfrom coma or not.Methods: We prospectively enrolled106comatose patients. Continuous EEG was startedas soon as possible after neurological intensive care unit (N-ICU) admission and wascontinuously recorded at least24hours. Each patient received1-month follow-up, duringwhich the Glasgow-Pittsburgh Cerebral Performance Categories (CPC) was used foroutcome assessment.Results:106comatose patients were included and monitored with continuous EEG. Theirmedian age was51years (range6–91years) and76patients (71.7%) were male.Forty-eight patients awoke according to the CPC scale on average12.7days after comaonset, and31died. EEG monitoring was commenced in the N-ICU between2h and3dafter admission and was technically successful in all patients, continuous EEG lasted amean of35±6hours. Univariate analysis showed that Glasow coma scale (GCS) score,Synek classification, EEG reactivity, sleep spindles and EEG-Coma were associated with1-month awakening. Comparisons of the ROC-AUCs showed that EEG-Coma (0.829;0.745–0.913) was superior to EEG reactivity, Sleep spindles, GCS score and Synek classification. Awakening was correctly predicted in83.3,65.0and71.6%, respectively,for EEG-Coma, EEG reactivity and sleep spindles. EEG-Coma, EEG reactivity and sleepspindles had very high specificity. While compared with EEG-Coma, EEG reactivity andsleep spindles showed a lower sensitivity and predicting value. EEG-Coma has both highsensitivity (80.0%) and high specificity (85.7%) in predicting awakening.Conclusions: EEG-Coma can predict outcome of comatose patients with a high predictiveaccuracy, although it needs to be further confirmed in a larger sample.